Bayesian inference is an appealing approach for leveraging prior knowledge in reinforcement learning (RL). In this paper we describe an algorithm for discovering different classes...
There are two main approaches, conservative and optimistic, for maintaining consistency in distributed network games. Under the conservative approach, players may experience netwo...
Affordances encode relationships between actions, objects and effects. They play an important role on basic cognitive capabilities such as prediction and planning. We address the p...
Luis Montesano, Manuel Lopes, Alexandre Bernardino...
We present GAMUT1 , a suite of game generators designed for testing game-theoretic algorithms. We explain why such a generator is necessary, offer a way of visualizing relationshi...
Eugene Nudelman, Jennifer Wortman, Yoav Shoham, Ke...
The quality of AI opponents often leaves a lot to be desired, which poses many attractive challenges for AI researchers. In this respect, Turn-based Strategy (TBS) games are of pa...